Coding & Dev Tools

holobiomicslab Skill

Use when you have raw metabolomics count data (e.g., from mass spectrometry or NMR experiments) in tabular format and associated sample metadata (e.g., treatment groups, experimental factors) that need to be imported into R for analysis with packages like Omu.

holobiomicslab Skill

Use when when starting with raw paired microbiome (16S rRNA, metagenomic taxonomic or functional features) and metabolome (LC-MS/MS, NMR) count tables from the same biospecimens, and planning to train prediction models or co-abundance networks.

holobiomicslab Skill

Use when after feature extraction and quality control filtering (blank masking, sample dropping, normalization) have been applied, but before statistical analysis or machine learning.

holobiomicslab Skill

Use when after data normalization (Step 7) when you have a preprocessed feature matrix and need to identify samples that deviate significantly from the multivariate center of the data distribution due to instrumental drift, batch effects, sample degradation, or genuine biological outliers that.

holobiomicslab Skill

Use when when you have cleaned and filtered mass spectrometry spectral data (in mzML, mzXML, msp, MGF, or JSON format) and need to identify or rank spectra by similarity for library matching, metabolite annotation, or network analysis.

holobiomicslab Skill

Use when you have multiple mass spectral library files in different formats (MSP, MGF, MOL folders) from sources like NIST, MoNA, RIKEN, or GNPS, and need to produce a single consolidated MSP file with complete SMILES, InChIKey, and experimental retention index (RI) annotations for metabolomics or.

holobiomicslab Skill

Use when after constructing a spectral similarity network from pairwise cosine similarity scores between deconvolved GC-MS spectra.

holobiomicslab Skill

Use when after MS-CleanR has filtered and clustered LC-MS features and formatted them for MS-FINDER input (m/z, retention time, MS/MS spectra).

holobiomicslab Skill

Use when you have processed LC-MS run data (feature table or peak detection output) containing internal standard identifications and need to monitor internal standard retention time, m/z, and intensity variation across samples as part of automated or user-defined QC checks during instrument runs.

holobiomicslab Skill

Use when you have a feature table containing raw ion mobility arrival time measurements paired with experimentally assigned biomolecular class labels (e.g., lipid, protein, carbohydrate), and you need to compute CCS values for downstream structural or comparative analysis.

holobiomicslab Skill

Use when you have a peak-picked feature table (HDF5 format with m/z, drift_time, retention_time, intensity columns) and need to identify and label isotopic signatures within singly charged species.

holobiomicslab Skill

Use when you have LC-HRMS raw data files (.mzML or .abf format) from metabolomics experiments and need to extract, align, and annotate features in a reproducible manner across multiple computational environments.

holobiomicslab Skill

Use when when you have a curated list of chemical compounds (real or virtual), a defined fragmentation strategy (e.g., Top-N, exclusion lists), and need to simulate how that strategy will acquire MS1 and MS2 scans over a defined retention-time window.

holobiomicslab Skill

Use when you have unaligned MS2 spectra from one or more samples (in formats like .mgf, .mzML, or .mzXML) and need to compare them in a retention-time-agnostic manner.

holobiomicslab Skill

Use when you have multiple mass spectral libraries in different formats (NIST MSP + MOL folder, MoNA MSP, RIKEN MSP, SWGDRUG MSP) and need to merge them into a single, MS-DIAL-compatible MSP file with consistent SMILES assignments, Kovats retention indices (RI), and polarity annotations across all.

holobiomicslab Skill

Use when after applying retention time, abundance correlation, or EIC similarity-based feature grouping (e.g., via SimilarRtimeParam, AbundanceSimilarityParam, or EicSimilarityParam). Use when you need to visually confirm that grouped features belong to the same compound—i.

holobiomicslab Skill

Use when you have raw DIA mass spectrometry files (.raw, .d, .wiff formats) from timsTOF, TripleTOF, or Orbitrap instruments and need to quantify file quality for automated quality control, longitudinal instrument monitoring, or training a quality prediction classifier.

holobiomicslab Skill

Use when you have extended a metabolite identification tool (such as Met-ID) to support a new derivatizing matrix beyond the default (e.

holobiomicslab Skill

Use when after feature detection and peak alignment have produced a feature table with zero or missing values across samples.

holobiomicslab Skill

Use when your m/z peak data spans multiple batches (recorded in metadata as a batch ID column) or samples have varying concentrations that are documented in metadata.

holobiomicslab Skill

Use when you have a set of query chemical compounds (as SMILES, names, or ChemMine objects) and a reference library organized into type groups (e.g., Type A–E chemical sets), and you need to assign each query compound to its -matching type based on structural similarity.

holobiomicslab Skill

Use when when you need to extract m/z and intensity peak values from a Spectra object backed by MsBackendMzR or similar on-disk backends; when analyzing subsets of spectra without loading all peaks into memory;

holobiomicslab Skill

Use when when you have a mass spectrometry data file (such as mzPeak) that has been read by two or more independent implementations (e.g., Rust, Python/pyarrow, R/arrow) and need to verify that all implementations produce identical spectrum metadata, data types, row counts, and numerical values.

holobiomicslab Skill

Use when immediately after parsing and validating raw LC-MS/MS data files (mzML, mzXML, or vendor formats) when you need to prepare spectral data for fragmentation tree computation, isotope pattern analysis, or molecular formula ranking within the SIRIUS framework.

holobiomicslab Skill

Use when when integrating LC-MS/MS data from diverse sources (e.g., public repositories like MSV000080102, instrument outputs, or precomputed workflows) into NPDtools pipelines.

holobiomicslab Skill

Use when you have QCpool (pooled quality control) samples measured at regular intervals across one or more LC-MS/MS sequences and need to detect whether instrument performance degrades, drifts, or destabilizes during the analytical run.

holobiomicslab Skill

Use when you have a ranked candidate list (e.g., BGCs sorted by IOKR or strain-correlation score) for each test spectrum, a known ground-truth BGC for each spectrum, and you want to measure retrieval performance across multiple recall depths (top-1 through top-200) and overall discrimination.

holobiomicslab Skill

Use when when you have MS/MS spectra with known chemical structures (InChIKeys or SMILES) and want to validate whether a novel or existing spectral similarity scoring method actually reflects true chemical structural similarity.

holobiomicslab Skill

Use when you have raw DIA mass spectrometry data files (.raw, .d, or .wiff formats) from timsTOF, TripleTOF, or Orbitrap instruments and need to extract precursor ion chromatograms for quality assessment or downstream analysis.

holobiomicslab Skill

Use when after loading an MsmsSpectrum object but before intensity filtering or spectral annotation.

holobiomicslab Skill

Use when after peak detection has been completed on individual LC-MS samples and you have a collection of detected peaks with m/z, retention time, and intensity values from each sample.

holobiomicslab Skill

Use when when you have implemented conditional routing logic in the GNPS_MASST codebase and need to verify that spectrum submissions with explicit domain-context selections (e.

holobiomicslab Skill

Use when you have computed a sparse pairwise distance matrix from nearest neighbor indexes (containing only cosine distances between neighboring spectra, not exhaustive pairwise comparisons) and need to partition spectra into groups of similar ions or peptides.

holobiomicslab Skill

Use when after loading raw m/z peak data (in MetaboAnalyst, MetaboShiny native, or Metabolights format) and merging it with sample metadata (batch IDs, concentration values, experimental group labels).

holobiomicslab Skill

Use when when comparing a query MS/MS spectrum (e.g., from an unknown metabolite) against a library spectrum to establish correspondence between peaks. Use this skill before calculating similarity scores (cosine, entropy, Bhattacharyya) or when applying penalty factors to unmatched peaks.

holobiomicslab Skill

Use when you have a query electron ionization (EI) mass spectrum and need to search it against a library of known EI mass spectra to identify unknown compounds. Use it when exact identity matching (e.